139 citations · 421 across the 12 of their papers we have counts for
4 papers · 1 filter
Contrastive Learning for Self-Supervised Pre-Training of Point Cloud Segmentation Networks With Image Data
Andrej Janda, Brandon Wagstaff, Edwin G. Ng +1
Reducing the quantity of annotations required for supervised training is vital when labels are scarce and costly. This reduction is particularly important for semantic segmentation…
Self-Supervised Pre-training of 3D Point Cloud Networks with Image Data
Andrej Janda, Brandon Wagstaff, Edwin G. Ng +1
Reducing the quantity of annotations required for supervised training is vital when labels are scarce and costly. This reduction is especially important for semantic segmentation t…
On the Coupling of Depth and Egomotion Networks for Self-Supervised Structure from Motion
Brandon Wagstaff, Valentin Peretroukhin, Jonathan Kelly
Structure from motion (SfM) has recently been formulated as a self-supervised learning problem, where neural network models of depth and egomotion are learned jointly through view…
Probabilistic Regression of Rotations using Quaternion Averaging and a Deep Multi-Headed Network
Valentin Peretroukhin, Brandon Wagstaff, Matthew Giamou +1
Accurate estimates of rotation are crucial to vision-based motion estimation in augmented reality and robotics. In this work, we present a method to extract probabilistic estimates…